Oilfield energy storage battery life monitoring and health state evaluation method and system

Abstract

The application discloses an oil field energy storage battery life monitoring and health state evaluation method and system, wherein the method comprises the following steps: when the current time enters a night mode, it is judged whether the current state of charge of the battery is within a set range, if yes, the next step is entered; an active thermal management mode of a battery management system is started, and the difference between the battery monomer temperature and the preset reference temperature is stabilized in a preset temperature range; after the temperature is stabilized in the preset temperature range, the battery is controlled to enter a constant current charging stage, and voltage-capacity data is synchronously collected; the IC curve is calculated according to the collected voltage-capacity data; the curve characteristics are extracted according to the IC curve; the curve characteristics comprise a half-width of a characteristic peak and a peak voltage offset; the extracted curve characteristics are input into a pre-labeled lookup table, the SOH value of the battery is obtained, and a corresponding early warning strategy or protection strategy is output according to the SOH value.

Description

Technical Field

[0001] This application relates to the field of battery life monitoring technology, and in particular to methods and systems for monitoring the life and assessing the health status of oilfield energy storage batteries. Background Technology

[0002] With the advancement of digital construction in oilfields, field oil production equipment (such as pumping unit controllers, wireless sensors, and RTUs) widely adopts a "photovoltaic + energy storage battery" power supply mode. Due to the harsh environment of oilfields, extreme temperature differences between day and night (up to 40°C), and the wide distribution and maintenance difficulties of the equipment, battery health status (SOH) monitoring has become crucial to ensuring the safety of oilfield production.

[0003] The inventors discovered that existing battery life monitoring technologies have the following drawbacks: Temperature interference is difficult to eliminate: Most existing SOH estimation methods are based on voltage or impedance measurements under natural temperature conditions. Although algorithm compensation is introduced, the accuracy of algorithm compensation is limited due to the uneven temperature distribution inside the battery and the nonlinearity of the electrochemical response, resulting in large estimation errors.

[0004] Low signal-to-noise ratio during testing: During the day, the photovoltaic charging current fluctuates greatly and the ripple interference is strong, making it difficult to extract accurate battery characteristic curves.

[0005] Lack of universal standards: The huge temperature difference in oil fields in different regions leads to inconsistent aging characteristic curves of the same battery in different regions, making it difficult to establish a unified life assessment standard. Summary of the Invention

[0006] To address the problems of existing technologies for oilfield energy storage batteries, such as large interference from diurnal temperature variations, lack of unified evaluation standards, and low detection accuracy, this application provides a method and system for monitoring the lifespan and assessing the health status of oilfield energy storage batteries. This system can eliminate temperature variables at the source and utilize stable nighttime operating conditions for high-precision lifespan monitoring.

[0007] On the one hand, it provides methods for monitoring the lifespan and assessing the health status of oilfield energy storage batteries, including: When entering night mode at the current time, determine whether the current state of battery charge is within the set range. If so, proceed to the next step. The active thermal management mode of the battery management system is activated to stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within the preset temperature range. Once the temperature stabilizes within the preset temperature range, the battery is controlled to enter the constant current charging stage, and voltage-capacity data is collected simultaneously. Based on the collected voltage-capacity data, calculate the IC curve; based on the IC curve, extract curve features; the curve features include: the full width at half maximum (FWHM) of the characteristic peak and the peak voltage offset; The extracted curve features are input into a pre-calibrated lookup table to obtain the SOH value of the battery, and corresponding early warning or protection strategies are output based on the SOH value.

[0008] On the other hand, it provides an oilfield energy storage battery life monitoring and health status assessment system, including: The judgment module is configured to: when entering night mode at the current time, determine whether the current state of charge of the battery is within the set range; if so, enter the thermal management module. The thermal management module is configured to: activate the active thermal management mode of the battery management system and stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within the preset temperature range. The charging module is configured to: control the battery to enter the constant current charging stage after the temperature stabilizes within the preset temperature range, and simultaneously collect voltage-capacity data. The feature extraction module is configured to: calculate the IC curve based on the collected voltage-capacity data; and extract curve features based on the IC curve; the curve features include: the full width at half maximum (FWHM) of the characteristic peaks and the peak voltage offset; The output module is configured to input the extracted curve features into a pre-calibrated lookup table to obtain the SOH value of the battery, and output corresponding early warning or protection strategies based on the SOH value.

[0009] Furthermore, an electronic device is also provided, including: Memory, used for non-transitory storage of computer-readable instructions; and Processor, for executing the computer-readable instructions, When the computer-readable instructions are executed by the processor, they perform the method described in the first aspect above.

[0010] In another aspect, a storage medium is also provided for non-transitory storage of computer-readable instructions, wherein when the non-transitory computer-readable instructions are executed by a computer, the method described in the first aspect is performed.

[0011] In another aspect, a computer program product is also provided, including a computer program that, when run on one or more processors, is used to implement the method described in the first aspect above.

[0012] The above technical solution has the following advantages or beneficial effects: Noise reduction at the source, extremely high accuracy: An isothermal testing environment is constructed through active temperature control, which completely eliminates temperature drift at the physical level. Compared with software compensation algorithms, accuracy and reliability are significantly improved.

[0013] Standardized and universally applicable: A unique universal standard curve has been established. Regardless of whether the battery is deployed in a cold northern oil field or a hot southern oil field, as long as the test method of this invention is followed, it can be evaluated based on the same standard curve, which greatly simplifies the difficulty of field deployment and maintenance.

[0014] The algorithm is lightweight and easy to deploy: It uses a lookup table method to replace complex neural networks or fuzzy logic operations, which requires very little computation and is fully compatible with existing low-power MCU chips in oil fields, thus reducing hardware costs.

[0015] Optimized detection window: High-precision detection is performed during the low-load period at night, avoiding interference from photovoltaic ripples during the day and ensuring the signal-to-noise ratio of data acquisition.

[0016] To eliminate the interference of temperature on battery aging characteristics at the physical level, an isothermal testing environment is constructed; high signal-to-noise ratio IC curve characteristic parameters (FWHM and voltage offset) are extracted during low-interference periods at night; a universal SOH evaluation standard curve is established to achieve rapid lifetime lookup without complex algorithms. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0018] Figure 1 This is a flowchart of the method in Example 1. Detailed Implementation

[0019] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0020] Terminology Explanation: IC curve (incremental capacity curve): refers to the curve showing how the derivative of capacity with respect to voltage (dQ / dV) changes with voltage during battery charging, used to characterize the phase transition characteristics inside the battery.

[0021] FWHM (half-width at half maximum): The width at half the peak value of the characteristic peak of the IC curve, used to quantify the degree of broadening of the characteristic peak.

[0022] State of Health (SOH): The ratio of the battery's current maximum usable capacity to its nominal capacity, used to measure the degree of battery aging.

[0023] Isothermal charging: refers to a test environment in which the battery temperature is strictly controlled at a constant value through active thermal management during the battery charging process.

[0024] TEC (Thermoelectric Cooler): A solid-state semiconductor device that uses the Peltier effect to achieve heating or cooling, characterized by vibration-free operation, fast response, and high temperature control accuracy.

[0025] PID control: Proportional-Integral-Derivative control algorithm, used to quickly and steadily stabilize the battery temperature near the target temperature.

[0026] Bilinear interpolation: A two-dimensional grid data interpolation method that calculates the value of any point within the grid through two linear interpolations, thereby improving the accuracy of table lookup.

[0027] Example 1 This embodiment provides a method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries. like Figure 1 As shown, the method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries includes: S101: When entering night mode at the current time, determine whether the current state of charge of the battery is within the set range. If so, proceed to S102. S102: Activate the active thermal management mode of the battery management system to stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within the preset temperature range. S103: Once the temperature stabilizes within the preset temperature range, control the battery to enter the constant current charging stage and simultaneously collect voltage-capacity data. S104: Calculate the IC curve based on the collected voltage-capacity data; extract curve features based on the IC curve; the curve features include: the full width at half maximum (FWHM) of the characteristic peak and the peak voltage offset; S105: Input the extracted curve features into a pre-calibrated lookup table to obtain the SOH value of the battery, and output the corresponding early warning strategy or protection strategy based on the SOH value.

[0028] Furthermore, the criteria for determining night mode in S101 include: When the output voltage of the photovoltaic panel connected to the battery is lower than the set threshold and continues to exceed the set time range, the current time is determined to be night mode.

[0029] Triggering condition: When the photovoltaic panel output voltage... If the voltage is below a threshold (e.g., 5V) and continues to exceed a set delay (e.g., 10 minutes), it is determined to be night mode.

[0030] Further, S101: determining whether the current state of charge of the battery is within the set range specifically includes: If the current state of charge is less than 20%, it is first charged to 30% with a current of 0.05C, and then proceeds to S102; If the current state of charge is greater than 80%, skip this test, record "Invalid test window", and wait until the following night to try again; If the current state of charge is greater than or equal to 20% and less than or equal to 80%, proceed directly to S102.

[0031] For example, before initiating the isothermal environment construction, the BMS first determines the current state of charge (SOC) of the battery: If SOC < 20%, precharge to 30% with a small current of 0.05C before proceeding to the isothermal build process; If SOC > 80%, skip this test, record "Invalid test window", and wait until the following night to try again; If SOC ∈ [20%, 80%], then proceed directly to the isothermal environment construction step. This mechanism avoids IC curve peak distortion caused by voltage plateau regions (low SOC or high SOC), ensuring the effectiveness of feature extraction.

[0032] Further, S102: Activating the active thermal management mode of the battery management system to stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within a preset temperature range, specifically including: When the temperature of a single battery cell is higher than the optimal reference temperature The battery management system (BMS) increases the positive current of the thermoelectric cooler (TEC), utilizes the Peltier effect to absorb battery heat, and dissipates it to the environment through the fins. When the temperature of a single battery cell is lower than the optimal reference temperature The battery management system reduces the positive current of the thermoelectric cooler or activates the auxiliary heating film to perform Joule heating on the battery. Compare the temperature of each battery cell with the preset optimal reference temperature. The absolute value of the difference is less than the set value; where the preset optimal reference temperature It equals the average of the highest and lowest historical temperatures in the oil field.

[0033] For example, the optimal reference temperature Settings: Settings A fixed value (preferably 25) C or 30 (C) This temperature should be higher than the lowest historical temperature in the oilfield but lower than the highest temperature to ensure the lowest possible energy consumption for thermal management.

[0034] For quantitative optimization The selection follows the principle of minimum energy consumption: Assume the lowest historical ambient temperature of the oil field is The highest historical ambient temperature was Then the optimal reference temperature satisfies:

[0035] Alternatively, 25℃ (the standard battery test temperature) can be used directly to balance energy consumption and the universality of the standard curve.

[0036] Temperature closed-loop control: PID algorithm is used to control the TEC to ensure that the battery temperature meets the following requirements throughout the entire IC curve scan:

[0037] The active thermal management module includes a thermoelectric cooler (TEC) attached to the surface of the battery cell and matching heat sink fins.

[0038] Cooling condition: When detected At this time, the BMS increases the forward current of the TEC, utilizes the Peltier effect to absorb battery heat and dissipates it to the environment through the fins; Heating condition: When heating is detected The BMS switches the TEC current direction or activates the auxiliary heating film (PI heating film) to perform Joule heating on the battery.

[0039] Temperature sampling frequency: To ensure temperature control accuracy, the temperature sampling frequency is not less than 1Hz, and the PID control cycle is synchronized with the BMS main control cycle.

[0040] Further, in step S103: after the temperature stabilizes within a preset temperature range, the battery is controlled to enter a constant current charging stage, and voltage-capacity data is collected simultaneously, specifically including: During the charging phase, the battery voltage and current are collected at a fixed sampling frequency; the current battery capacitance is calculated using the ampere-hour integration method.

[0041] For example, the objective is to extract aging-sensitive micro-features from charging data.

[0042] Data acquisition: During overnight charging, data is collected at a fixed sampling frequency. Collect battery terminal voltage and current .

[0043] Capacity calculation: The current capacity is calculated using the ampere-hour integration method. :

[0044] in, This is the initial charging capacity.

[0045] Further, in step S104: Calculate the IC curve based on the collected voltage-capacity data; extract curve features based on the IC curve; the curve features include: the full width at half maximum (FWHM) of the characteristic peak and the peak voltage offset, specifically including: The IC curve is obtained based on the derivative of capacitance with respect to voltage. Gaussian function curves are obtained by fitting Gaussian curves to discrete points within a 50mV voltage range on both sides of the main peak of the IC curve. The peak voltage of the main characteristic peak is then determined using the fitted Gaussian function curves. ; The peak voltage offset is obtained by calculating the difference between the peak voltage of a new battery with 100% state of charge at the same temperature and the fitted peak voltage. ; Calculate the voltage range width at half the peak value of the main characteristic peak, and use it as the half-width at half-maximum (FWHM).

[0046] Furthermore, obtaining the IC curve based on the derivative of capacitance with respect to voltage specifically includes: calculate Since the actual data consists of discrete points, the finite difference method is used for approximation:

[0047] Further, the step of performing Gaussian fitting on discrete points near the main peak of the IC curve to obtain the fitted main characteristic peak and peak voltage includes: To improve the stability of feature parameter extraction, discrete points within a 50mV voltage range on both sides of the main peak of the IC curve were analyzed. Perform Gaussian fitting, fitting function for:

[0048] in, Peak height coefficient; The peak voltage after fitting; This is the peak width parameter; This is the baseline offset.

[0049] The relationship between the full width at half maximum (FWHM) and the Gaussian fitting parameter σ is as follows:

[0050] Compared to the direct difference extraction method, Gaussian fitting can effectively suppress the interference of data noise on the localization of feature peaks. The extraction error was reduced from ±10mV to ±2mV.

[0051] Furthermore, the difference between the peak voltage of a new battery with a state of charge of 100% at the same temperature and the fitted peak voltage is used to obtain the peak voltage offset. Specifically, it includes: Peak voltage offset: Select the voltage value corresponding to the main characteristic peak of the IC curve. Calculate the difference between it and the new battery (SOH=100%) at the same temperature. .

[0052] Furthermore, the calculation of the voltage range width at half the peak value of the main characteristic peak, as the full width at half maximum (FWHM), specifically includes: Half-width at half-maximum (FWHM): The width of the voltage range at half the peak value of the main characteristic peak. .

[0053] in, and These represent the values ​​on the main characteristic peak, when the ordinate... The left and right voltage values ​​corresponding to half the peak value, i.e.:

[0054] in, The peak value of the main characteristic peak.

[0055] Further, step S105: inputting the extracted curve features into a pre-calibrated lookup table, specifically includes: Select a battery sample group that is the same model and batch as the battery to be tested; Accelerated aging tests were performed on each battery in the battery sample group; Record the characteristic parameters under different charge-discharge cycle numbers; The least squares method is used to process the feature parameters to obtain a three-dimensional mapping model; The three-dimensional mapping model is discretized into a two-dimensional lookup table.

[0056] Furthermore, the formula for the three-dimensional mapping model is:

[0057] Alternatively, a quadratic polynomial form can be used:

[0058] Where SOH represents the battery health status (0~100%), and SOH is the output of the model; It is the peak voltage offset. It is one of the inputs to the model; It is half the height and width. It is one of the inputs to the model; These are linear regression coefficients, obtained through least squares fitting. These are the quadratic regression coefficients, obtained through least squares fitting.

[0059] Discretizing the three-dimensional mapping model into a two-dimensional lookup table means: The range of values ​​is divided into discrete points, The range of values ​​is divided into For each discrete grid point, calculate the value. corresponding form The two-dimensional lookup table is stored in the BMS's memory.

[0060] For example, step S105: inputting the extracted curve features into a pre-calibrated lookup table specifically includes: Sample selection: Select battery sample groups of the same model and batch ( (Number of units), covering the entire lifecycle of this battery model.

[0061] Accelerated aging test: in a constant temperature chamber The sample is subjected to cyclic charge-discharge aging at ambient temperature. An IC curve scan is performed after each preset number of cycles (e.g., 100 cycles).

[0062] Feature database construction: Recording different loop counts (corresponding to different...) Feature parameters under ) (FWHM), to remove outlier data points.

[0063] Fitting the mapping relationship: Establish a three-dimensional mapping model using the least squares method or polynomial regression. The model is discretized into a two-dimensional lookup table and stored in the non-volatile memory of the BMS.

[0064] The formula for the three-dimensional mapping model is:

[0065] Alternatively, a quadratic polynomial form can be used:

[0066] The specific method of discretization is as follows: First step, determine and The range of values ​​for . Based on experimental data, let . , .

[0067] The second step is to divide the two value ranges into m and n equally spaced discrete points respectively:

[0068]

[0069] The third step is to set each set of discrete points Substitute into the three-dimensional mapping model Calculate the corresponding

[0070]

[0071] The fourth step is to store the above calculation results as a single... A two-dimensional array (lookup table) is stored in the BMS's memory. In field applications, the actual measured values... The corresponding SOH value is obtained from the lookup table using bilinear interpolation.

[0072] in, yes The number of discrete points in the direction; yes The number of discrete points in the direction; It is an actual measurement Minimum value; It is an actual measurement Maximum value; It is an actual measurement Minimum value; It is an actual measurement Maximum value.

[0073] Calibration process: Under laboratory conditions, for batteries of the same model, Under constant temperature conditions, its aging at different degrees was tested. From 100% to the failure threshold) The FWHM curve is plotted as a two-dimensional standard curve and discretized into a look-up table, which is then embedded in the BMS chip.

[0074] Further, in step S105: the extracted curve features are input into a pre-calibrated lookup table to obtain the battery's... Values, specifically including: The battery is calculated using a bilinear interpolation algorithm. value.

[0075] Field applications: Field devices do not require complex neural network calculations; they only need to process the measured data. By mapping coordinates to a lookup table, the current coordinates can be interpolated and calculated. Value. Since all tests are conducted in... The standard curve is applicable to all batteries of the same model and has strong universality.

[0076] Since the lookup table stores discrete grid points corresponding The results were obtained from on-site measurements. Typically located between grids, bilinear interpolation is used for calculation. : Set up the measured points The four corner points of the grid it is located at are , , , The corresponding SOH value is , , .

[0077] First Directional linear interpolation:

[0078]

[0079] Then in Directional linear interpolation:

[0080] in, It is the peak voltage offset at the measured point. ; Half-width at the measured point ; These are the left and right boundary points of the grid where the measured point is located. Value, and ; These are the lower and upper boundary points of the grid where the measured point is located. Value, and ; For grid points The pre-calibrated SOH value; Grid points The pre-calibrated SOH value; Grid points The pre-calibrated SOH value; Grid points The pre-calibrated SOH value; yes The intermediate value obtained after the first interpolation of the direction; yes The intermediate value obtained after the second interpolation of the direction; This is the final output of the battery health status.

[0081] This interpolation method can achieve the desired result without increasing storage space. Output accuracy is improved to within 1 / 10 of the lookup table grid spacing.

[0082] Further, S105: according to The output value corresponds to the early warning or protection strategy, specifically including: Early warning mechanism: If the calculated (e.g., 80%), the BMS sends a battery replacement warning to the monitoring center via the wireless communication module.

[0083] Adaptive protection: If The BMS automatically limits the maximum depth of discharge (DOD) for the next day to prevent irreversible damage to aging batteries under low temperature or high current conditions.

[0084] Furthermore, in the final output Before setting the value, add a trend filtering step: The result of this calculation Perform a first-order lag filter on the results of the previous N (N=3) detections:

[0085] The value of α is between 0.3 and 0.5. This filter can prevent SOH jumps caused by abnormalities in a single test, thus avoiding false alarms.

[0086] Further, in step S104: calculating the IC curve based on the collected voltage-capacity data; after extracting curve features based on the IC curve, in step S105: inputting the extracted curve features into a pre-calibrated lookup table to obtain the battery's SOH value; and before outputting the corresponding early warning or protection strategy based on the SOH value, the method further includes: S104-5: Data Validation: To avoid misjudgments under extreme operating conditions, this method adds a data verification step before performing the SOH assessment: Temperature consistency verification: If the battery temperature fluctuates by more than ±1.0 degrees Celsius during IC curve acquisition, the test is deemed invalid, the data is discarded, and the temperature control process is restarted.

[0087] Curve shape verification: Calculate the peak area (total capacity) of the acquired IC curve. If the peak area deviates from the available capacity under the current SOC state by more than 5%, it is determined that the acquired signal is interfered with, and the retry mechanism is initiated (maximum 3 retryes).

[0088] Example 2 This embodiment provides an oilfield energy storage battery life monitoring and health status assessment system, including: The judgment module is configured to: when entering night mode at the current time, determine whether the current state of charge of the battery is within the set range; if so, enter the thermal management module. The thermal management module is configured to: activate the active thermal management mode of the battery management system and stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within the preset temperature range. The charging module is configured to: control the battery to enter the constant current charging stage after the temperature stabilizes within the preset temperature range, and simultaneously collect voltage-capacity data. The feature extraction module is configured to: calculate the IC curve based on the collected voltage-capacity data; and extract curve features based on the IC curve; the curve features include: the full width at half maximum (FWHM) of the characteristic peaks and the peak voltage offset; The output module is configured to input the extracted curve features into a pre-calibrated lookup table to obtain the SOH value of the battery, and output corresponding early warning or protection strategies based on the SOH value.

[0089] It should be noted that the aforementioned judgment module, thermal management module, charging module, feature extraction module, and output module correspond to steps S101 to S105 in Embodiment 1. The examples and application scenarios implemented by these modules and their corresponding steps are the same, but they are not limited to the content disclosed in Embodiment 1. It should also be noted that these modules, as part of the system, can be executed in a computer system, such as a set of computer-executable instructions.

[0090] The descriptions of each embodiment in the above embodiments have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0091] The proposed system can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and the division of modules described above is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed.

[0092] Example 3 This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory to cause the electronic device to perform the method described in Embodiment 1.

[0093] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0094] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0095] In the implementation process, each step of the above method can be completed by the integrated logic circuits in the processor hardware or by software instructions.

[0096] The method in Embodiment 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0097] Those skilled in the art will recognize that the units and algorithm steps described in conjunction with the embodiments herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0098] Example 4 This embodiment also provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the method described in Embodiment 1.

[0099] Example 5 This embodiment also provides a computer program product, including a computer program that, when executed by a processor, implements the method in Embodiment 1.

[0100] This application also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0101] The computer program code used to implement the methods of this application may be written in one or more programming languages. This computer program code may be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0102] In the context of this application, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0103] Those skilled in the art will recognize that the units and algorithm steps described in conjunction with the embodiments herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0104] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries, characterized by: include: When entering night mode at the current time, determine whether the current state of battery charge is within the set range. If so, proceed to the next step. The active thermal management mode of the battery management system is activated to stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within the preset temperature range. Once the temperature stabilizes within the preset temperature range, the battery is controlled to enter the constant current charging stage, and voltage-capacity data is collected simultaneously. Calculate the IC curve based on the collected voltage-capacity data; Extract curve features based on the IC curve; The curve features include: the full width at half maximum (FWHM) of the characteristic peak and the peak voltage offset; The extracted curve features are input into a pre-calibrated lookup table to obtain the SOH value of the battery, and corresponding early warning or protection strategies are output based on the SOH value.

2. The method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries as described in claim 1, characterized in that, The criteria for determining night mode include: when the output voltage of the photovoltaic panel connected to the battery is lower than a set threshold and continues for more than a set time range, the current time is determined to be night mode; Determining whether the battery's current state of charge is within the set range specifically includes: If the current state of charge is less than 20%, it will first be charged to 30% with a current of 0.05C, and then enter the active thermal management mode of the battery management system. If the current state of charge is greater than 80%, skip this test, record "Invalid test window", and wait until the following night to try again; If the current state of charge is greater than or equal to 20% and less than or equal to 80%, the active thermal management mode of the battery management system will be activated directly.

3. The method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries as described in claim 1, characterized in that, The active thermal management mode of the battery management system is activated to stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within a preset temperature range. Specifically, this includes: When the temperature of a single battery cell is higher than the optimal reference temperature The battery management system (BMS) increases the positive current of the thermoelectric cooler (TEC), utilizes the Peltier effect to absorb battery heat, and dissipates it to the environment through the fins. When the temperature of a single battery cell is lower than the optimal reference temperature The battery management system reduces the positive current of the thermoelectric cooler or activates the auxiliary heating film to perform Joule heating on the battery. Compare the temperature of each battery cell with the preset optimal reference temperature. The absolute value of the difference is less than the set value; where the preset optimal reference temperature It equals the average of the highest and lowest historical temperatures in the oil field.

4. The method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries as described in claim 1, characterized in that, Once the temperature stabilizes within the preset range, the battery enters the constant current charging phase, simultaneously collecting voltage-capacity data. Specifically, during the charging phase, the battery voltage and current are collected at a fixed sampling frequency; and the current battery capacitance is calculated using the ampere-hour integration method. Calculate the current capacity using the ampere-hour integral method. : in, This is the initial charging capacity.

5. The method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries as described in claim 1, characterized in that, Calculate the IC curve based on the collected voltage-capacity data; Extract curve features based on the IC curve; The curve features include: the full width at half maximum (FWHM) of the characteristic peak and the peak voltage offset, specifically including: The IC curve is obtained based on the derivative of capacitance with respect to voltage. Gaussian function curves are obtained by fitting Gaussian curves to discrete points within a 50mV voltage range on both sides of the main peak of the IC curve. The peak voltage of the main characteristic peak is then determined using the fitted Gaussian function curves. ; The peak voltage offset is obtained by calculating the difference between the peak voltage of a new battery with 100% state of charge at the same temperature and the fitted peak voltage. ; Calculate the voltage range width at half the peak value of the main characteristic peak, and use it as the full width at half maximum (FWHM). Discrete points within a 50mV voltage range on both sides of the main peak of the IC curve Perform Gaussian fitting, fitting function for: in, Peak height coefficient; The peak voltage after fitting; This refers to the peak width parameter; Baseline offset; The difference between the peak voltage of a new battery with a state of charge of 100% at the same temperature and the fitted peak voltage is used to obtain the peak voltage offset. Specifically, it includes: Peak voltage offset: Select the voltage value corresponding to the main characteristic peak of the IC curve. Calculate the difference between it and the new battery at the same temperature. ; The calculation of the voltage range width at half the peak value of the main characteristic peak, as the full width at half maximum (FWHM), specifically includes: calculating the voltage range width at half the peak value of the main characteristic peak. ; in, and These represent the left and right voltage values ​​corresponding to the ordinate being half the peak value at the main characteristic peak: in, The peak value of the main characteristic peak.

6. The method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries as described in claim 1, characterized in that, The extracted curve features are input into a pre-defined lookup table, specifically including: Select a battery sample group of the same model and batch as the battery to be tested; conduct accelerated aging tests on each battery in the battery sample group; record the characteristic parameters under different charge-discharge cycles; use the least squares method to process the characteristic parameters to obtain a three-dimensional mapping model; discretize the three-dimensional mapping model into a two-dimensional lookup table; The formula for the three-dimensional mapping model is: Alternatively, a quadratic polynomial form can be used: Where SOH represents the battery health state, and SOH is the output of the model; It is the peak voltage offset. It is one of the inputs to the model; It is half the height and width. It is one of the inputs to the model; These are linear regression coefficients, obtained through least squares fitting. These are quadratic regression coefficients, obtained through least squares fitting. Discretizing the three-dimensional mapping model into a two-dimensional lookup table means: The range of values ​​is divided into discrete points, The range of values ​​is divided into For each discrete grid point, calculate the value. corresponding form The two-dimensional lookup table is stored in the BMS's memory.

7. The method for monitoring the lifespan and assessing the health status of oilfield energy storage batteries as described in claim 1, characterized in that, The extracted curve features are input into a pre-calibrated lookup table to obtain the battery's... The values ​​specifically include: the battery's... (The sentence is incomplete and requires more context to translate accurately.) value; according to The output value corresponds to the early warning or protection strategy, specifically including: Early warning mechanism: If the calculated The BMS sends a battery replacement warning to the monitoring center via the wireless communication module; Adaptive protection: If The BMS automatically limits the maximum depth of discharge the next day to prevent irreversible damage to aging batteries under low temperature or high current conditions. Furthermore, in the final output Before calculating the value, add a trend filtering step: This step involves applying the calculated value... Perform a first-order lag filter on the results of N historical detections: Where α ranges from 0.3 to 0.5; Based on the collected voltage-capacity data, the IC curve is calculated. After extracting curve features from the IC curve, these features are input into a pre-calibrated lookup table to obtain the battery's SOH value. Before outputting corresponding early warning or protection strategies based on the SOH value, the process also includes: data validity verification. Temperature consistency verification: If the battery temperature fluctuates by more than ±1.0 degrees Celsius during IC curve acquisition, the test is deemed invalid, the data is discarded, and the temperature control process is restarted. Curve shape verification: Calculate the peak area of ​​the acquired IC curve. If the peak area deviates from the available capacity under the current SOC state by more than 5%, it is determined that the acquired signal is interfered with, and the retry mechanism is initiated.

8. An oilfield energy storage battery life monitoring and health status assessment system, characterized in that: include: The judgment module is configured to: when entering night mode at the current time, determine whether the current state of charge of the battery is within the set range; if so, enter the thermal management module. The thermal management module is configured to: activate the active thermal management mode of the battery management system and stabilize the difference between the temperature of the individual battery cells and the preset reference temperature within the preset temperature range. The charging module is configured to: control the battery to enter the constant current charging stage after the temperature stabilizes within the preset temperature range, and simultaneously collect voltage-capacity data. The feature extraction module is configured to calculate the IC curve based on the collected voltage-capacity data. Extract curve features based on the IC curve; The curve features include: the full width at half maximum (FWHM) of the characteristic peak and the peak voltage offset; The output module is configured to input the extracted curve features into a pre-calibrated lookup table to obtain the SOH value of the battery, and output corresponding early warning or protection strategies based on the SOH value.

9. An electronic device, characterized in that it comprises: Memory is used to store computer-readable instructions in a non-transitory manner. as well as Processor, for executing the computer-readable instructions, When the computer-readable instructions are executed by the processor, they perform the method described in any one of claims 1-7.

10. A storage medium, characterized in that, Non-transitory storage of computer-readable instructions, wherein when the non-transitory computer-readable instructions are executed by a computer, the method of any one of claims 1-7 is performed.

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